DNA BARCODING AND PHYLOGENETIC RELATIONSHIP OF RAY-FINNED FISH FAMILY SERRANIDAE (GENUS EPINEPHELUS) FROM THE COAST OF GWADAR BALUCHISTAN
Bibliographic record
Abstract
DNA barcoding is inevitable for identification and effectively replacing the traditional pattern of species taxonomy around the world. Species of the family Serranidae are commercially important and play a vital role in Pakistan economy. This family is in high demand in both domestic and international markets due to its white, tender, and flavorful meat, as well as its appealing texture, generating significant revenue. Many species exhibit close morphological characteristics, leading to confusion in accurate identification. The objectives of present study are to identify the grouper species based on morphological and molecular approaches. Epinephelus fish samples were collected with the assistance of local fisherman from the coast of Gawadar, Baluchistan. Besides the morphological identification approaches, the barcoding method became an integral tool for identification in by years and it replacing the traditional taxonomic approaches worldwide. In present study we became successful to identify the four species of Epinephelus, however the genetic distance revealed a diversity range of 0.00 to 0.19. Furthermore, the phylogenetic analysis detailed the close relationship between the species from China, Iraq, Iran, Malaysia, Bangladesh, India, Qatar, Saudi Arabia, Thailand, Canada and Tehran. Key words: DNA barcoding, Phylogenetic relationship, Epinephelus, N.J. (neighbor joining), Kimura distance, Gwadar
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".